Question

我有以下数据框：

              Profit       Cumulative
Date                            
1/6/2005    248.8500      248.85
1/12/2005    48.3500      297.20
1/13/2005    29.2900      326.49
1/13/2005  -500.0000     -173.51
1/13/2005  -250.9500     -424.46
1/14/2005   126.6600     -297.80
1/16/2005    58.7400     -239.06
1/19/2005    68.3500     -170.71
1/21/2005   140.0000      -30.71
1/23/2005   200.0000      169.29
1/26/2005  -250.6800      -81.39
1/27/2005   162.5000       81.11
1/27/2005   135.5100      216.62
1/27/2005  -650.0000     -433.38
1/28/2005    96.8800     -336.50
1/28/2005 -1000.0000    -1336.50
1/31/2005   140.0000    -1196.50
2/1/2005    140.0000    -1056.50

第一列是我投资组合的美元利润。我用以下公式计算了第二列：

df['Cumulative'] = df.Profit.cumsum().round(2)

那么，有没有一个公式可以计算出我的投资组合的美元（而非％）数量？该列应如下所示：

Drawdonwn

 0.00
 0.00
 0.00
-500.00
-750.95
-624.29
-565.55
-497.20
-357.20
-157.20
-407.88
-245.38
-109.87
-759.87
-662.99
-1,662.99
-1,522.99
-1,382.99
-1,382.99

Answer 1

df['Cumulative'] = df.Profit.cumsum().round(2)
df['HighValue'] = df['Cumulative'].cummax()

df['Drawdown'] = df['Cumulative'] - df['HighVal']

这是我能找到的最简单的解决方案。

Answer 2

根据我的记忆，亏损是指您的投资组合利润低于高额的金额。（将来，你应该明确定义你想要的输出，不要让人们知道你在问什么。）

可能有更好的方法，但您可以使用pandas在itertuples()中计算出来：

import pandas as pd
from StringIO import StringIO

# read the data
df = pd.DataFrame.from_csv(StringIO("""Date               Profit       Cumulative
1/6/2005    248.8500      248.85
1/12/2005    48.3500      297.20
1/13/2005    29.2900      326.49
1/13/2005  -500.0000     -173.51
1/13/2005  -250.9500     -424.46
1/14/2005   126.6600     -297.80
1/16/2005    58.7400     -239.06
1/19/2005    68.3500     -170.71
1/21/2005   140.0000      -30.71
1/23/2005   200.0000      169.29
1/26/2005  -250.6800      -81.39
1/27/2005   162.5000       81.11
1/27/2005   135.5100      216.62
1/27/2005  -650.0000     -433.38
1/28/2005    96.8800     -336.50
1/28/2005 -1000.0000    -1336.50
1/31/2005   140.0000    -1196.50
2/1/2005    140.0000    -1056.50"""), sep="\s+").reset_index()

# calculate drawdown
prev_high = 0
for i, date, profit, cumulative in df.itertuples():
    prev_high = max(prev_high, cumulative)
    dd = cumulative - prev_high
    df.loc[i, 'Drawdown'] = dd if dd < 0 else 0

结果数据框：

>>> print(df)
         Date   Profit  Cumulative  Drawdown
0  2005-01-06   248.85      248.85      0.00
1  2005-01-12    48.35      297.20      0.00
2  2005-01-13    29.29      326.49      0.00
3  2005-01-13  -500.00     -173.51   -500.00
4  2005-01-13  -250.95     -424.46   -750.95
5  2005-01-14   126.66     -297.80   -624.29
6  2005-01-16    58.74     -239.06   -565.55
7  2005-01-19    68.35     -170.71   -497.20
8  2005-01-21   140.00      -30.71   -357.20
9  2005-01-23   200.00      169.29   -157.20
10 2005-01-26  -250.68      -81.39   -407.88
11 2005-01-27   162.50       81.11   -245.38
12 2005-01-27   135.51      216.62   -109.87
13 2005-01-27  -650.00     -433.38   -759.87
14 2005-01-28    96.88     -336.50   -662.99
15 2005-01-28 -1000.00    -1336.50  -1662.99
16 2005-01-31   140.00    -1196.50  -1522.99
17 2005-02-01   140.00    -1056.50  -1382.99

Investopedia对drawdown的定义。

计算熊猫的缩编

2 个答案: